Xingjian Bai

Undergraduate @ Oxford

Incoming PhD student @ MIT

Email: xbai AT mit.edu

I am an undergraduate student at Oxford, pursuing a degree in Mathematics and Computer Science. My research primarily explores the intersection of classic algorithms and modern optimisation algorithms, including topics such as learning-augmented algorithms and the theoretical foundations of optimisation models. I am motivated to conduct research that has the potential of making a significant scientific impact.

During my time at Oxford, I have had the privilege of working with Prof. Jan Obloj, Prof. Christian Coester, Prof. Christian Rupprecht, and Luke Melas-Kyriazi. I also spent a rewarding summer at Stanford, collaborating with Prof. Jiajun Wu, Dr. Weiyu Liu, and Joy Hsu. Outside of my academic pursuits, I enjoy jogging and playing tennis. I also engage in algorithmic programming competitions.

Collaborators: I am eager to learn from and collaborate with individuals from diverse backgrounds. If you would like to discuss something, I would be grateful to hear from you. Please feel free to contact me via email or schedule a time to chat through Chatting Time.

News:

Feb 2024: Our paper, Fixed Point Diffusion Models, is accepted at CVPR'24!

Unweighted Layered Graph Traversal

Xingjian Bai, Christian Coester, Romain Cosson

In submission

arXiv

@misc{bai2024unweighted,
      title={Unweighted Layered Graph Traversal}, 
      author={Xingjian Bai and Christian Coester and Romain Cosson},
      year={2024},
      eprint={2404.16176},
      archivePrefix={arXiv},
      primaryClass={cs.DS}
}

Fixed Point Diffusion Models

Xingjian Bai*, Luke Melas-Kyriazi*

(*equal contribution)

Computer Vision and Pattern Recognition (CVPR), 2024

page

arXiv

code

@InProceedings{bai2024fixed,
    title={Fixed Point Diffusion Models},
    author={Xingjian Bai and Luke Melas-Kyriazi},
    booktitle = {CVPR},
    year = {2024}
}

Goodhart's Law in Reinforcement Learning

Jacek Karwowski, Oliver Hayman, Xingjian Bai, Charlie Griffin, Joar Skalse

International Conference on Learning Representations (ICLR), 2023

arXiv

@InProceedings{karwowski2023goodharts,
    title={Goodhart's Law in Reinforcement Learning}, 
    author={Jacek Karwowski and Oliver Hayman and Xingjian Bai and Klaus Kiendlhofer and Charlie Griffin and Joar Skalse},
    year={2024},
    booktitle = {ICLR},
}

Sorting with Predictions

Xingjian Bai, Christian Coester

Conference on Neural Information Processing Systems (NeurIPS), 2023

arXiv

poster

code

@InProceedings{bai2023sorting,
    title={Sorting with Predictions}, 
    author={Xingjian Bai and Christian Coester},
    booktitle = {NeurIPS},
    year = {2023}
}

Wasserstein Distributional Robustness of Neural Networks

Xingjian Bai, Guangyi He, Yifan Jiang, Jan Obloj

Conference on Neural Information Processing Systems (NeurIPS), 2023

arXiv

poster

code

@InProceedings{bai2023wasserstein,
    title={Wasserstein distributional robustness of neural networks}, 
    author={Xingjian Bai and Guangyi He and Yifan Jiang and Jan Obloj},
    year={2023},
    booktitle = {NeurIPS},
}

Xingjian Bai

PUBLICATIONS

Unweighted Layered Graph Traversal

Fixed Point Diffusion Models

Goodhart's Law in Reinforcement Learning

Sorting with Predictions

Wasserstein Distributional Robustness of Neural Networks

CHATTING TIME